Service assurance techniques have a significant role in the management of large Enterprise and Service Provider Networks. There are a number of standard as well as vendor proprietary techniques to choose from to accomplish tasks like connectivity testing, response time analysis, path monitoring, etc. One problem is that testing is relatively difficult and resource intensive to deploy and can cause scalability problems if tests are not designed correctly. One example of this is connectivity testing between sites in an enterprise network. Testing with even a relatively modest number of sites (like 100) can create almost 10,000 tests in a single poll cycle when a full mesh test architecture is used. One of the challenges of this situation is that most tests are created by hand—one at a time. Although network management systems may automate some aspect of test creation and analysis, there is still a significant scaling problem.
Many tests are, deployed either one at a time or “en masse,” with neither approach providing optimal coverage. The process of creating one test at a time may never yield appropriate coverage, while bulk creation may waste resources by provisioning tests indiscriminately.
Another concern in deploying service assurance testing is the possibility of test scale impacting network operations and performance negatively. Other difficulties may also exist.
Thus, provisioning and deployment of optimal testing that provides appropriate coverage for the environment, the equipment, performance goals and/or assurance level required by the enterprise or user is desirable.